Solar powered thermal energy storage systems are known. Some systems have mechanisms for varying the amount of sunlight incident on a solar energy collector to regulate the amount of thermal energy being stored. Furthermore, many thermal energy storage systems are not limited in the amount of thermal energy which may be stored.
A space vehicle solar energy thermally powered electrical generating system is not a conventional application of solar energy. It is not desirable to directly regulate the amount of solar energy being absorbed by a thermal storage medium in a spacecraft because of the complexity of the requisite controls Furthermore because of the high energy content of solar energy above the earth's atmosphere and the limited size of the thermal energy storage medium in a space vehicle, the maximum thermal capacity of the thermal storage medium may be exceeded during periods of insolation. It is known that electric power systems for aerospace applications may be controlled utilizing state estimation and control principles. See "An Integrated Analytic Tool and Knowledge-Based System Approach to Aerospace Electric Power System Control", October, 1986, Society of Aeronautical Engineers Conference by William R. Owens, Eric Henderson and Kapal Gandikota. As described therein, state estimation is used to compute the state of the system from measurement of system variables with the state estimation being used for controlling the system.
Furthermore, it is known that actual system performance may be controlled by mathematically modeling system components to be controlled with differential equations when data is insufficient to control system performance by conventional control principles. This technique is known as "Kalman" filtering. See "A New Approach to Linear Filtering and Prediction Problems", R. E. Kalman, Journal of Basic Engineering, March 1960, pp 35-45 and "New Results in Linear Filtering and Prediction Theory", Journal of Basic Engineering, March, 1961, pp 95-107 by R. E. Kalman and R. S. Bucy. Kalman filtering has been utilized to perform estimation and prediction of unmeasured variables in a system to be controlled. See "Estimation and Prediction of Unmeasured Variables in Steel Mill Soaking Pit Control System", IEEE Transactions on Automatic Control, Vol. AC-28, pp 372-380, March, 1983 by V. Lumelsky. Additional publications describing further applications of Kalman filtering are "Applied Optical Estimation", The MIT Press, Cambridge, Mass., 1974 by A. Gelb and "IEEE Transactions on Automatic Control" Vol. AC-16, No. 6, December, 1976.
U.S. Pat. Nos. 4,577,270 and 4,635,182 disclose examples of Kalman filtering used in control systems in which insufficient data exists to calculate a state estimate based on conventional control principles using measured data. Kalman filtering theory may be applied to provide state estimations when insufficient data exists for using conventional control theory in those situations when it is possible to mathematically model by differential equations the component parts of the system to be controlled. Kalman filtering theory is applicable to both current and future state estimates with the future state estimate being based upon extrapolating the differential equations used to mathematically model the current state estimate into the future.
Heat pipes with integral thermal energy storage have been utilized by the Los Alamos National Laboratory in thermal energy storage systems. The Arizona State University has verified that a sodium heat pipe with lithium hydroxide thermal energy canisters successfully functions as a thermal energy storage medium. The lithium hydroxide thermal energy storage medium is characterized by a solid phase which has a first linear relationship between the change in heat (Q) and the change of temperature (T) which has a relatively high slope. Once sufficient energy is absorbed by the lithium hydroxide system, the solid phase begins to change state to a liquid state. The relationship of Q versus T in the state in which there is a phase change to the liquid state is characterized by a second linear relatively small slope in which large amounts of heat may be added to the lithium hydroxide without substantially changing the temperature of the thermal storage medium. Finally, once all of the lithium hydroxide storage medium has changed to the liquid state, the relationship of Q versus T increases again at relatively high slope.
There is no known way of directly measuring the actual heat stored in the lithium hydroxide system during operation in the second slope because of the small slope with the analogy being measuring the amount of electrical energy stored in a storage battery. Moreover, it is undesirable to operate the thermal energy storage medium in either the first or third slopes of the Q versus T characteristic.